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Open Access
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nThis is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.n
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Prashant Roy,
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- Student, Department of Engineering, Banaras Hindu University, Varanasi, Uttar Pradesh, India
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Abstract
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nThe field of robotics has experienced significant advancements in both kinematic and dynamic design, driven by the growing need for precision, adaptability, and autonomy in mechanical systems. Early robotic mechanisms were predominantly rigid and operated based on simple serial architectures, offering limited degrees of freedom and relying heavily on analytical formulations for motion planning and control. Over time, the demand for greater dexterity and operational versatility led to the development of parallel, redundant, and reconfigurable mechanisms. These advancements enabled improvements in workspace utilization, force distribution, and motion accuracy. Kinematic design has evolved from classical Denavit–Hartenberg-based modeling to modern approaches incorporating optimization algorithms, artificial intelligence, and learning-based strategies. Redundant manipulators and flexible joints have allowed robots to perform complex tasks in constrained environments. On the dynamic front, the progression from basic Newton-Euler and Lagrangian formulations to sophisticated real-time control algorithms, including model predictive control, impedance control, and adaptive force regulation, has significantly enhanced performance in terms of responsiveness and robustness. The integration of compliant elements, soft materials, and bio-inspired actuation has introduced new paradigms in safety and human-robot interaction. Furthermore, the adoption of digital twins, simulation platforms, and AI-driven model learning has minimized the dependency on exact physical modeling and enabled faster iterations in design and control. This review systematically explores the historical trajectory, current state, and emerging trends in the kinematic and dynamic design of robotic mechanisms. It highlights the core methodologies, technical challenges, and transformative innovations shaping next-generation robotic systems. The paper also addresses the practical implications of these developments across industries such as manufacturing, healthcare, space exploration, and service robotics. By offering a comprehensive synthesis of past and present advancements, this work aims to support future research and the continued evolution of intelligent robotic systems.nn
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Keywords: DH convention, recursive Newton-Euler algorithms, articulated-body algorithm, soft robotics, robotic mechanisms, kinematics, dynamics, parallel manipulators, trajectory optimization, adaptive control, AI in robotics
n[if 424 equals=”Regular Issue”][This article belongs to Trends in Machine design ]
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nPrashant Roy. [if 2584 equals=”][226 wpautop=0 striphtml=1][else]Evolution of Kinematic and Dynamic Design in Robotic Mechanisms: A Systematic Overview[/if 2584]. Trends in Machine design. 30/07/2025; 12(02):38-43.
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nPrashant Roy. [if 2584 equals=”][226 striphtml=1][else]Evolution of Kinematic and Dynamic Design in Robotic Mechanisms: A Systematic Overview[/if 2584]. Trends in Machine design. 30/07/2025; 12(02):38-43. Available from: https://journals.stmjournals.com/tmd/article=30/07/2025/view=0
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| Volume | 12 | |
| [if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] | 02 | |
| Received | 09/07/2025 | |
| Accepted | 19/07/2025 | |
| Published | 30/07/2025 | |
| Retracted | ||
| Publication Time | 21 Days |
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